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Journal of Bioinformatics and Computational Biology

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https://www.readbyqxmd.com/read/29157072/robustness-versus-evolvability-analysis-for-regulatory-feed-forward-loops
#1
Debika Choudhury, Amit Agarwal, Supreet Saini
From the definition, it appears that phenotypic robustness and evolvability of an organism are inversely related to each other. However, a number of studies exploring this question have found conflicting evidences in this regard. This question motivated the current work where we explore the relationship between robustness and evolvability. As a model system, we pick the Feed Forward Loops (FFLs), and develop a framework to characterize their performance in terms of their ability to resist changes to steady state expression (robustness), and their ability to evolve towards novel phenotypes (evolvability)...
November 3, 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29113564/evaluating-the-quality-of-shape-data-simulated-by-k-mers-for-rna-structure-prediction
#2
Soheila Montaseri, Fatemeh Zare-Mirakabad, Mohammad Ganjtabesh
Finding an effective measure to predict a more accurate RNA secondary structure is a challenging problem. In the last decade, an experimental method, known as selective [Formula: see text]-hydroxyl acylation analyzed by primer extension (SHAPE), was proposed to measure the tendency of forming a base pair for almost all nucleotides in an RNA sequence. These SHAPE reactivities are then utilized to improve the accuracy of RNA structure prediction. Due to a significant impact of SHAPE reactivity and in order to reduce the experimental costs, we propose a new model called HL-k-mer...
October 19, 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29113562/utilizing-networks-for-differential-analysis-of-chromatin-interactions
#3
Lu Liu, Jianhua Ruan
Chromatin conformation capture with high-throughput sequencing (Hi-C) is a powerful technique to detect genome-wide chromatin interactions. In this paper, we introduce two novel approaches to detect differentially interacting genomic regions between two Hi-C experiments using a network model. To make input data from multiple experiments comparable, we propose a normalization strategy guided by network topological properties. We then devise two measurements, using local and global connectivity information from the chromatin interaction networks, respectively, to assess the interaction differences between two experiments...
October 19, 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29113560/efficient-rna-structure-comparison-algorithms
#4
Abdullah N Arslan, Jithendar Anandan, Eric Fry, Keith Monschke, Nitin Ganneboina, Jason Bowerman
Recently proposed relative addressing-based ([Formula: see text]) RNA secondary structure representation has important features by which an RNA structure database can be stored into a suffix array. A fast substructure search algorithm has been proposed based on binary search on this suffix array. Using this substructure search algorithm, we present a fast algorithm that finds the largest common substructure of given multiple RNA structures in [Formula: see text] format. The multiple RNA structure comparison problem is NP-hard in its general formulation...
October 19, 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29113563/multidimensional-knowledge-based-framework-is-an-essential-step-in-the-categorization-of-gene-sets-in-complex-disorders
#5
A Sreeja, K P Vinayan
In complex disorders, collaborative role of several genes accounts for the multitude of symptoms and the discovery of molecular mechanisms requires proper understanding of pertinent genes. Majority of the recent techniques utilize either single information or consolidate the independent outlook from multiple knowledge sources for assisting the discovery of candidate genes. In any case, given that various sorts of heterogeneous sources are possibly significant for quality gene prioritization, every source bearing data not conveyed by another, we assert that a perfect strategy ought to give approaches to observe among them in a genuine integrative style that catches the degree of each, instead of utilizing a straightforward mix of sources...
October 9, 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29113561/metagenome-sequence-clustering-with-hash-based-canopies
#6
Mohammad Arifur Rahman, Nathan LaPierre, Huzefa Rangwala, Daniel Barbara
Metagenomics is the collective sequencing of co-existing microbial communities which are ubiquitous across various clinical and ecological environments. Due to the large volume and random short sequences (reads) obtained from community sequences, analysis of diversity, abundance and functions of different organisms within these communities are challenging tasks. We present a fast and scalable clustering algorithm for analyzing large-scale metagenome sequence data. Our approach achieves efficiency by partitioning the large number of sequence reads into groups (called canopies) using hashing...
October 9, 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28982289/selected-papers-from-the-16th-international-conference-on-bioinformatics-incob-2017
#7
Tatsuya Akutsu
No abstract text is available yet for this article.
October 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28982288/mptm-a-tool-for-mining-protein-post-translational-modifications-from-literature
#8
Dongdong Sun, Minghui Wang, Ao Li
Due to the importance of post-translational modifications (PTMs) in human health and diseases, PTMs are regularly reported in the biomedical literature. However, the continuing and rapid pace of expansion of this literature brings a huge challenge for researchers and database curators. Therefore, there is a pressing need to aid them in identifying relevant PTM information more efficiently by using a text mining system. So far, only a few web servers are available for mining information of a very limited number of PTMs, which are based on simple pattern matching or pre-defined rules...
October 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28918707/wdnfinder-a-method-for-minimum-driver-node-set-detection-and-analysis-in-directed-and-weighted-biological-network
#9
Yanshuo Chu, Zhenxing Wang, Rongjie Wang, Ningyi Zhang, Jie Li, Yang Hu, Mingxiang Teng, Yadong Wang
Structural controllability is the generalization of traditional controllability for dynamical systems. During the last decade, interesting biological discoveries have been inferred by applied structural controllability analysis to biological networks. However, false positive/negative information (i.e. nodes and edges) widely exists in biological networks that documented in public data sources, which can hinder accurate analysis of structural controllability. In this study, we propose WDNfinder, a comprehensive analysis package that provides structural controllability with consideration of node connection strength in biological networks...
October 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28893113/an-empirical-bayes-method-for-robust-variance-estimation-in-detecting-degs-using-microarray-data
#10
Na You, Xueqin Wang
The microarray technology is widely used to identify the differentially expressed genes due to its high throughput capability. The number of replicated microarray chips in each group is usually not abundant. It is an efficient way to borrow information across different genes to improve the parameter estimation which suffers from the limited sample size. In this paper, we use a hierarchical model to describe the dispersion of gene expression profiles and model the variance through the gene expression level via a link function...
October 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28877645/bone-marrow-cavity-segmentation-using-graph-cuts-with-wavelet-based-texture-feature
#11
Hironori Shigeta, Tomohiro Mashita, Junichi Kikuta, Shigeto Seno, Haruo Takemura, Masaru Ishii, Hideo Matsuda
Emerging bioimaging technologies enable us to capture various dynamic cellular activities [Formula: see text]. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on...
October 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28874087/systematic-investigations-of-gene-effects-on-both-topologies-and-supports-an-echinococcus-illustration
#12
Christophe Guyeux, Stéphane Chrétien, Nathalie M-L Côté, Jacques M Bahi
In this paper, we propose a high performance computing toolbox implementing efficient statistical methods for the study of phylogenies. This toolbox, which implements logit models and LASSO-type penalties, gives a way to better understand, measure, and compare the impact of each gene on a global phylogeny. As an application, we study the Echinococcus phylogeny, which is often considered as a particularly difficult example. Mitochondrial and nuclear genomes (19 coding sequences) of nine Echinococcus species are considered in order to investigate the molecular phylogeny of this genus...
October 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28874086/pacluster-clustering-polyadenylation-site-data-using-canonical-correlation-analysis
#13
Guoli Ji, Qianmin Lin, Yuqi Long, Congting Ye, Wenbin Ye, Xiaohui Wu
Alternative polyadenylation (APA) is a pervasive mechanism that contributes to gene regulation. Increasing sequenced poly(A) sites are placing new demands for the development of computational methods to investigate APA regulation. Cluster analysis is important to identify groups of co-expressed genes. However, clustering of poly(A) sites has not been extensively studied in APA, where most APA studies failed to consider the distribution, abundance, and variation of APA sites in each gene. Here we constructed a two-layer model based on canonical correlation analysis (CCA) to explore the underlying biological mechanisms in APA regulation...
October 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28513252/a-novel-model-based-on-fcm-lm-algorithm-for-prediction-of-protein-folding-rate
#14
Longlong Liu, Mingjiao Ma, Jing Cui
The prediction of protein folding rates is of paramount importance in describing the protein folding mechanism, which has broad applications in fields such as enzyme engineering and protein engineering. Therefore, predicting protein folding rates using the first-order of protein sequence, secondary structure and amino acid properties has become a very active research topic in recent years. This paper presents a new fuzzy cognitive map (FCM) model based on deep learning neural networks which uses data obtained from biological experiments to predict the protein folding rate...
August 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28718343/application-of-t-sne-to-human-genetic-data
#15
Wentian Li, Jane E Cerise, Yaning Yang, Henry Han
The t-distributed stochastic neighbor embedding t-SNE is a new dimension reduction and visualization technique for high-dimensional data. t-SNE is rarely applied to human genetic data, even though it is commonly used in other data-intensive biological fields, such as single-cell genomics. We explore the applicability of t-SNE to human genetic data and make these observations: (i) similar to previously used dimension reduction techniques such as principal component analysis (PCA), t-SNE is able to separate samples from different continents; (ii) unlike PCA, t-SNE is more robust with respect to the presence of outliers; (iii) t-SNE is able to display both continental and sub-continental patterns in a single plot...
June 23, 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28659000/recurrent-neural-network-based-modeling-of-gene-regulatory-network-using-elephant-swarm-water-search-algorithm
#16
Sudip Mandal, Goutam Saha, Rajat Kumar Pal
Correct inference of genetic regulations inside a cell from the biological database like time series microarray data is one of the greatest challenges in post genomic era for biologists and researchers. Recurrent Neural Network (RNN) is one of the most popular and simple approach to model the dynamics as well as to infer correct dependencies among genes. Inspired by the behavior of social elephants, we propose a new metaheuristic namely Elephant Swarm Water Search Algorithm (ESWSA) to infer Gene Regulatory Network (GRN)...
June 13, 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28610458/large-scale-parallel-genome-assembler-over-cloud-computing-environment
#17
Arghya Kusum Das, Praveen Kumar Koppa, Sayan Goswami, Richard Platania, Seung-Jong Park
The size of high throughput DNA sequencing data has already reached the terabyte scale. To manage this huge volume of data, many downstream sequencing applications started using locality-based computing over different cloud infrastructures to take advantage of elastic (pay as you go) resources at a lower cost. However, the locality-based programming model (e.g. MapReduce) is relatively new. Consequently, developing scalable data-intensive bioinformatics applications using this model and understanding the hardware environment that these applications require for good performance, both require further research...
June 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28571482/introduction-to-selected-papers-from-the-8th-international-conference-on-bioinformatics-and-computational-biology-bicob-2016
#18
Nurit Haspel, Thomas Ioerger, Hisham Al-Mubaid
No abstract text is available yet for this article.
June 1, 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28610459/an-automated-pipeline-for-mitochondrial-segmentation-on-atum-sem-stacks
#19
Weifu Li, Hao Deng, Qiang Rao, Qiwei Xie, Xi Chen, Hua Han
It is possible now to look more closely into mitochondrial physical structures due to the rapid development of electron microscope (EM). Mitochondrial physical structures play important roles in both cellular physiology and neuronal functions. Unfortunately, the segmentation of mitochondria from EM images has proven to be a difficult and challenging task, due to the presence of various subcellular structures, as well as image distortions in the sophisticated background. Although the current state-of-the-art algorithms have achieved some promising results, they have demonstrated poor performances on these mitochondria which are in close proximity to vesicles or various membranes...
May 26, 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28571483/an-efficient-method-for-significant-motifs-discovery-from-multiple-dna-sequences
#20
Abdulrakeeb M Al-Ssulami, Aqil M Azmi, Hassan Mathkour
Identification of transcription factor binding sites or biological motifs is an important step in deciphering the mechanisms of gene regulation. It is a classic problem that has eluded a satisfactory and efficient solution. In this paper, we devise a three-phase algorithm to mine for biologically significant motifs. In the first phase, we generate all the possible string motifs, this phase is followed by a filtering process where we discard all motifs that do not meet the constraints. And in the final phase, motifs are scored and ranked using a combination of stochastic techniques and [Formula: see text]-value...
May 11, 2017: Journal of Bioinformatics and Computational Biology
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